olivhoenen · Jun 17, 2026 · Feb 27, 2026 · Mar 3, 2026 · Mar 26, 2026 · Apr 1, 2026
@@ -0,0 +1,10 @@
+version: 2
+updates:
+  # Enable version updates for Github Actions
+  - package-ecosystem: "github-actions"
+    # Look for `/.github/workflows` and `/action.yml` or `.yaml`
+    directory: "/"
+    # Check for updates once a week
+    schedule:
+      interval: "weekly"
+
@@ -12,10 +12,10 @@ jobs:
 
     steps:
       - name: Checkout IMAS-Python sources
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Python
-        uses: actions/setup-python@v5
+        uses: actions/setup-python@v6
         with:
           # until saxonche is available in 3.13
           # https://saxonica.plan.io/issues/6561

@@ -10,11 +10,11 @@ jobs:
     name: Build distribution
     runs-on: ubuntu-22.04
     steps:
-    - uses: actions/checkout@v4
+    - uses: actions/checkout@v6
       with:
         fetch-depth: 0 
     - name: Set up Python
-      uses: actions/setup-python@v5
+      uses: actions/setup-python@v6
       with:
         # until saxonche is available in 3.13
         # https://saxonica.plan.io/issues/6561
@@ -25,7 +25,7 @@ jobs:
     - name: Build a binary wheel and a source tarball
       run: python3 -m build .
     - name: Store the distribution packages
-      uses: actions/upload-artifact@v4
+      uses: actions/upload-artifact@v7
       with:
         name: python-package-distributions
         path: dist/
@@ -43,7 +43,7 @@ jobs:
       id-token: write  # IMPORTANT: mandatory for trusted publishing
     steps:
     - name: Download all the dists
-      uses: actions/download-artifact@v4
+      uses: actions/download-artifact@v8
       with:
         name: python-package-distributions
         path: dist/
@@ -63,7 +63,7 @@ jobs:
       id-token: write  # IMPORTANT: mandatory for trusted publishing
     steps:
     - name: Download all the dists
-      uses: actions/download-artifact@v4
+      uses: actions/download-artifact@v8
       with:
         name: python-package-distributions
         path: dist/

@@ -14,11 +14,11 @@ jobs:
 
     steps:
       - name: Checkout repository
-        uses: actions/checkout@v4
+        uses: actions/checkout@v6
 
       - name: Set up Python ${{ matrix.python-version }}
 
-        uses: actions/setup-python@v4
+        uses: actions/setup-python@v6
         with:
           python-version: ${{ matrix.python-version }}
       - name: Display Python version
@@ -37,13 +37,13 @@ jobs:
           python -m pytest -n=auto --cov=imas --cov-report=term-missing --cov-report=xml:coverage.xml --cov-report=html:htmlcov --junit-xml=junit.xml
 
       - name: Upload coverage report ${{ matrix.python-version }}
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v7
         with:
           name: coverage-report-${{ matrix.python-version }}
           path: htmlcov
 
       - name: Upload test report ${{ matrix.python-version }}
-        uses: actions/upload-artifact@v4
+        uses: actions/upload-artifact@v7
         with:
           name: test-report-${{ matrix.python-version }}
           path: junit.xml
@@ -20,4 +20,4 @@ python:
 sphinx:
   builder: html
   configuration: docs/source/conf.py
-  fail_on_warning: false
+  fail_on_warning: true
@@ -34,6 +34,9 @@
 author = "ITER Organization"
 src_host = "https://github.com/iterorganization/"
 
+# Warn about missing references
+nitpicky = True
+
 # Parse urls here for convenience, to be re-used
 # ITER docs
 iter_projects = "https://github.com/iterorganization/"

@@ -14,13 +14,16 @@ enumerated list of options for defining, for example:
 - These may have alternative naming conventions supported through aliases 
   (e.g., "235U" and "U_235" for Uranium 235).
 
-Identifiers are a list of possible valid labels. Each label has up to four
-representations:
+Identifiers are a list of possible valid options. Each option has three representations
+that are stored in an IDS:
 
 1. An index (integer)
 2. A name (short string)
 3. A description (long string)
-4. List of aliases (list of short strings)
+
+.. seealso::
+    `Data Dictionary documentation for identifiers
+    <https://imas-data-dictionary.readthedocs.io/en/latest/identifiers.html>`__
 
 
 Identifiers in IMAS-Python
@@ -32,6 +35,20 @@ constructed on-demand from the loaded Data Dictionary definitions.
 All identifier enums can be accessed through ``imas.identifiers``. A list of
 the available identifiers is stored as ``imas.identifiers.identifiers``.
 
+Each identifier option provides the following attributes:
+
+- ``name``: the name of the option.
+- ``index``: the integer index value of the option.
+- ``description``: a longer string describing the option.
+- ``aliases``: a list of aliases that can be used instead of the name.
+- ``units``: optional information about the units of the quantities that are affected by
+  the identifier option. Take, for example, the `poloidal plan coordinate identifier
+  <https://imas-data-dictionary.readthedocs.io/en/stable/generated/identifier/poloidal_plane_coordinates_identifier.html>`__
+  which affects the units of ``grid/dim1`` and ``grid/dim2``.
+
+.. versionadded:: 2.1.0 ``aliases`` for identifiers.
+.. versionadded:: 2.3.0 ``units`` metadata.
+
 .. code-block:: python
     :caption: Accessing identifiers
 
@@ -47,6 +64,9 @@ the available identifiers is stored as ``imas.identifiers.identifiers``.
     print(csid.total.index)
     print(csid.total.description)
 
+    # Search identifier options by their index value
+    print(csid(1))
+
     # Access identifiers with aliases (when available)
     mid = imas.identifiers.materials_identifier
     print(mid["235U"].name)        # Access by canonical name
@@ -57,12 +77,12 @@ the available identifiers is stored as ``imas.identifiers.identifiers``.
     assert mid["235U"].name is mid.U_235.name
 
     # Item access is also possible
-    print(identifiers["edge_source_identifier"])
+    print(imas.identifiers["edge_source_identifier"])
 
     # You can use imas.util.inspect to list all options
-    imas.util.inspect(identifiers.ggd_identifier)
+    imas.util.inspect(imas.identifiers.ggd_identifier)
     # And also to get more details of a specific option
-    imas.util.inspect(identifiers.ggd_identifier.SN)
+    imas.util.inspect(imas.identifiers.ggd_identifier.SN)
 
     # When an IDS node is an identifier, you can use
     # metadata.identifier_enum to get the identifier
@@ -186,6 +206,7 @@ material_identifier["235U"].
     mat.names[0] = mid.U_235.name  # enum value via alias
     mat.names[0] = mid["U_235"].name  # enum value via alias
 
+
 Compare identifiers
 -------------------
 

@@ -86,17 +86,6 @@ get an error message if this is not possible:
 Load and store an IDS to disk with IMAS-Core
 ''''''''''''''''''''''''''''''''''''''''''''
 
-.. note::
-
-    - This functionality requires the IMAS-Core, until this library is openly available
-      on GitHub you may need to fetch it from `git.iter.org <https://git.iter.org/>`_
-      (requires to have an ITER account). Using IMAS-Core also enable slicing methods
-      :py:meth:`~imas.db_entry.DBEntry.get_slice`, 
-      :py:meth:`~imas.db_entry.DBEntry.put_slice` and
-      :py:meth:`~imas.db_entry.DBEntry.get_sample` (with IMAS-Core>=5.4).
-    - If you can't have access to it, you can save IDS to disk with the built-in
-      netCDF backend :ref:`Load and store an IDS to disk with netCDF`
-
 To store an IDS to disk, we need to indicate the following URI to the
 IMAS-Core: ``imas:<backend>?path=<path_to_folder>`` or using the legacy query keys
 ``imas:<backend>?user=<user>;database=<database>;version=<version>;pulse=<pulse>;run=<run>``
@@ -115,11 +104,9 @@ In IMAS-Python you do this as follows:
     >>> # now store the core_profiles IDS we just populated
     >>> dbentry.put(core_profiles)
 
-.. image:: imas_structure.png
-
 To load an IDS from disk, you need to specify the same information as
 when storing the IDS (see above). Once the data entry is opened, you
-can use ``<IDS>.get()`` to load IDS data from disk: 
+can use ``dbentry.get()`` to load IDS data from disk: 
 
 .. code-block:: python
 
@@ -146,11 +133,34 @@ In IMAS-Python you do this as follows:
 
 To load an IDS from disk, you need to specify the same file information as
 when storing the IDS. Once the data entry is opened, you
-can use ``<IDS>.get()`` to load IDS data from disk: 
+can use ``dbentry.get()`` to load IDS data from disk: 
 
 .. code-block:: python
 
     >>> # Now load the core_profiles IDS back from disk
     >>> dbentry2 = imas.DBEntry("mypulsefile.nc","r")
     >>> core_profiles2 = dbentry2.get("core_profiles")
     >>> print(core_profiles2.ids_properties.comment.value)
+
+
+Data Entry API overview
+'''''''''''''''''''''''
+
+See the documentation of :py:class:`imas.DBEntry <imas.db_entry.DBEntry>` for more
+details on reading and writing IDSs to disk. Useful functions include:
+
+- :py:meth:`~imas.db_entry.DBEntry.put` and :py:meth:`~imas.db_entry.DBEntry.put_slice`
+  to write a full IDS or write append a time slice to existing data.
+- :py:meth:`~imas.db_entry.DBEntry.get`, :py:meth:`~imas.db_entry.DBEntry.get_slice` and
+  :py:meth:`~imas.db_entry.DBEntry.get_sample` to read all time slices, a single time
+  slice, or a sample of time slices from disk. ``get_slice()`` and ``get_sample()`` can
+  also interpolate data to a requested point in time.
+
+  All three ``get()`` methods have a ``lazy`` mode, which will only load data from disk
+  when you need it. This can greatly speed up data access in some scenarios. See
+  :ref:`Lazy loading` for more details.
+- :py:meth:`~imas.db_entry.DBEntry.list_all_occurrences` to query whether there are any
+  occurrences of a certain IDS stored on disk.
+- :py:meth:`~imas.db_entry.DBEntry.list_filled_paths` to query which Data Dictionary
+  paths have data filled inside a specific IDS.
+
@@ -290,24 +290,17 @@ you may see the following error:
   Dictionary version of the DBEntry (3.42.0). This is not supported when using the
   UDA backend.
 
-There are three possible workarounds. The first two require passing an additional option
+There are two possible workarounds. The first one requires passing an additional option
 in the IMAS UDA URI: please see the `imas-core documentation
 <https://imas-core.readthedocs.io/en/stable/user_guide/backends_guide.html#query-keys-specific-for-the-uda-backend>`__
-for more details on these URI options.
+for more details on URI options.
 
 1. Use UDA fetch to bypass the cache problem. You can do this by appending ``&fetch=1``
    to the URI when you create the :py:class:`~imas.db_entry.DBEntry`.
 
    Note that this will download the entire IDS files from the remote server, this may
    not be desired if you only want to read a single time slice.
-2. Disable the UDA cache. You can do this by appending ``&cache_mode=none`` to the URI
-   when you create the :py:class:`~imas.db_entry.DBEntry`.
-
-   Note that this may make the ``get()`` (a lot) slower, since a separate request needs
-   to be sent to the remote UDA server for every data variable. However, this may still
-   be the best performing option if you are only interested in a subset of all the data
-   in an IDS (and use :ref:`lazy loading`).
-3. Explicitly provide the data dictionary version when you create the
+2. Explicitly provide the data dictionary version when you create the
    :py:class:`~imas.db_entry.DBEntry`, setting it to match the Data Dictionary version
    of the data you want to load. To obtain the version of the data on the remote server
    from the field `ids_properties.put_version.data_dictionary` via a _lazy_ ``get()``
@@ -316,7 +309,7 @@ for more details on these URI options.
    Note that you may need to call ``imas.convert_ids`` to convert the IDS to your
    desired Data Dictionary version.
 
-All three possible workarounds are shown in the examples below:
+The two possible workarounds are shown in the examples below:
 
 .. md-tab-set::
 
@@ -346,20 +339,7 @@ All three possible workarounds are shown in the examples below:
         with imas.DBEntry(URI, "r") as entry:
             cp = entry.get("core_profiles")
 
-    .. md-tab-item:: 2. Disable the UDA cache
-
-      .. code-block:: python
-
-        import imas
-
-        URI = (
-            "imas://uda.iter.org:56565/uda?backend=hdf5"
-            "&path=/work/imas/shared/imasdb/ITER/3/121013/50&cache_mode=none"
-        )
-        with imas.DBEntry(URI, "r") as entry:
-            cp = entry.get("core_profiles")
-
-    .. md-tab-item:: 3. Explicitly provide the DD version
+    .. md-tab-item:: 2. Explicitly provide the DD version
 
       .. code-block:: python